Iterative methods are greedy or local in nature and get easily trapped in local optima. Usually interchange methods fail to converge to optimal solutions unless they initially begin from good starting points. The choice of starting point is a very crucial factor in the performance of the iterative improvement algorithms [1]. GRASP is a random adaptive simple heuristic that intelligently constructs good initial solutions in an efficient manner. Good initial partitions obtained by GRASP allow theiterative improvement method to refine that initial partition quality in a reasonable amount of time, thus reducing the computational time and enhancing the solution quality. Results obtained indicate that on average the cut-size is reduced by 20% andspeedups of up to 90% were achieved using the GRASP technique.
展开▼
